Artificial Intelligence (IT4042E) Quang Nhat Nguyen quang.nguyennhat@hust.edu.vn Hanoi University of Science and Technology School of Information and Communication Technology Academic Year 2020-2021
Content: ◼ Introduction of Artificial Intelligence ❑ Definition ❑ Foundation fields ❑ Brief history ❑ Successful practical applications ❑ Software frameworks and libraries ◼ Intelligent agent ◼ Problem solving: Search, Constraint satisfaction ◼ Logic and reasoning ◼ Knowledge representation ◼ Machine learning Artificial Intelligence 2
Definition of AI (1) ◼ The definitions (i.e., point of view) of Artificial Intelligence (AI) can be categorized in 4 groups: ❑ (1) Systems that think like humans ◼ " The exciting new effort to make computers think ... machines with minds, in the full and literal sense ." (Haugeland, 1985) ◼ " [The automation of] activities that we associate with human thinking, activities such as decision-making, problem solving, learning ..." (Bellman, 1978) ❑ (2) Systems that think rationally ◼ " The study of mental faculties through the use of computational models ." (Charniak and McDermott, 1985) ◼ " The study of the computations that make it possible to perceive, reason, and act ." (Winston, 1992) Artificial Intelligence 3
Definition of AI (2) ❑ (3) System that act like humans ◼ " The art of creating machines that perform functions that require intelligence when performed by people ." (Kurzweil, 1990) ◼ " The study of how to make computers do things at which, at the moment, people are better ." (Rich and Knight, 1991) ❑ (4) System that act rationally ◼ " Computational Intelligence is the study of the design of intelligent agents ." (Poole et al., 1998) ◼ " AI . . .is concerned with intelligent behavior in artifacts ." (Nilsson, 1998) Artificial Intelligence 4
Definition of AI (3) ◼ The definitions (1) and (2) relate to thinking and inference processes ◼ The definitions (3) and (4) relate to actions ◼ The definitions (1) and (3) assess the success (i.e., intelligence) at the level of human intelligence ◼ The definitions (2) and (4) assess the success (i.e., intelligence) at the level of rationality ❑ A system is considered acting rationally if it does its jobs according to what it (the system) knows ❑ Artificial Intelligence (AI) is the science and engineering of making intelligent machines, especially intelligent computer programs [John McCarthy, Stanford University , http://www- formal.stanford.edu/jmc/whatisai/node1.html ] Artificial Intelligence 5
Acting humanly: Turing test Turing (1950) “Computing machinery and intelligence": ◼ “Can machines think?" → “Can machines behave intelligently?" ◼ Operational test for intelligent behavior: the Imitation Game ◼ Predicted that by 2000, a machine might have a 30% chance of surpassing a non-expert person for a Turing test in 5 minutes ◼ Anticipated (by 1950) all major arguments against AI in following 50 years ◼ Suggested major components of AI: knowledge, reasoning, language understanding, learning Artificial Intelligence 6
Acting rationally ◼ Rational behavior : Doing the right thing ◼ The right thing : That which is expected to maximize goal achievement, given the available information ◼ Doesn't necessarily involve thinking ❑ E.g., blinking reflex ◼ But thinking should be in the service of rational action ◼ The rationality should take the computation cost into account ❑ If the computation resource and time costs are too high, then it is impractical (i.e., not applicable in practice) Artificial Intelligence 7
Rational agents (1) ◼ An agent is an entity that perceives and acts ◼ Abstractly, an agent is a function from percept histories to actions: f : P* → A Artificial Intelligence 8
Rational agents (2) ◼ For an environment and a task, we need to find out an agent that has the best performance ◼ An intelligent agent is the one that can act rationally (i.e., intelligently) Action that helps maximize the achievement of the goal(s), given the ❑ perceived information ◼ Important note: Limits of computation (of the computer) do not allow perfect (optimal) rationality to be achieved → Intelligence vs. computation cost (practicality) Artificial Intelligence 9
Foundation fields of AI (1) ◼ Philosophy ❑ Logic ❑ Methods of reasoning ❑ Foundations of learning ❑ Language ❑ Rationality ◼ Mathematics ❑ Formal representation and Proof algorithms ❑ Computation ❑ Decidable vs. undecidable problems ❑ Tractable vs. intractable problems (i.e., computational complexity, especially time cost) ❑ Probability Artificial Intelligence 10
Foundation fields of AI (2) ◼ Economics ❑ Utility function ❑ Decision making theory ◼ Neuroscience ❑ Natural basis of mental activities ◼ Psychology ❑ Adaptivity ❑ Phenomena of perception and motor control ❑ Experimental techniques (psychophysics, etc.) Artificial Intelligence 11
Foundation fields of AI (3) ◼ Computer technology ❑ Build high-speed computers ❑ High performance computing ◼ Control theory ❑ Design systems to maximize a certain objective function ◼ Linguistics ❑ Knowledge representation ❑ Grammar (of a language) Artificial Intelligence 12
Brief history of AI (1) ◼ 1943: McCulloch & Pitts presented the first research on AI, which proposed modeling of two-state (i.e., on/off) artificial neurons ◼ 1950: The concept of AI was first mentioned by Turing in his article "Computing Machinery and Intelligence" ◼ 1956 : The first workshop (taking place in 2 months) in Dartmouth (USA) discussing the field of AI, the concept of AI was admitted ◼ 1952-1969: The initial achievements in AI ◼ 1950s: First AI programs ❑ Samuel's chess program ❑ Newell & Simon's logic reasoning program ❑ Gelernter’s geometric theorem proving program Artificial Intelligence 13
Brief history of AI (2) ◼ 1965: Robinson proposed the complete algorithm for logic reasoning ◼ 1966-1973: ❑ AI researchers realized the difficulty of computational complexity ❑ Artificial neural networks are heavily influenced, and are developed very slowly ◼ 1969-1979: Introduction and early development of knowledge-based systems ◼ 1980: AI became an industry (AI systems and programs were used commercially) ◼ 1980-1988: The emergence of expert systems ◼ 1986: Artificial neural networks re-appeared, became popularly ◼ 1987: AI became a scientific field ◼ 1995: Introduction of intelligent agents Artificial Intelligence 14
The main research areas of AI ◼ Constraints and satisfiability ◼ Heuristic search and Game playing ◼ Knowledge representation and reasoning ◼ Machine learning (including Deep learning) ◼ Data mining ◼ Planning and Scheduling ◼ Natural language processing ◼ Robotics ◼ Computer vision ◼ Agent-based and Multi-agent systems Artificial Intelligence 15
Important achievements in AI (1) ◼ Information retrieval ❑ Virtual assistant: Siri, Google Now, Cortana, Bixby, etc. ◼ Human-machine communication ❑ Voice, Gesture, Natural language understanding, etc. Artificial Intelligence 16
Important achievements in AI (2) ◼ Entertainment ❑ Music, Movies, Games, News, Social networks, etc. ◼ Transportation ❑ Shelf-driving car, Traffic law enforcement, Prediction of demand for car/motorbike ride, etc. Artificial Intelligence 17
Important achievements in AI (3) ◼ Education and learning ❑ Learning materials, Learning path, Knowledge dissemination, etc. ◼ E-commerce ❑ Product/service recommendations, Demand prediction, Promotion campaign, etc. Artificial Intelligence 18
Important achievements in AI (4) ◼ System security ❑ Computer virus detection, Network intrusion detection, Email spam filtering, etc. ◼ Marketing and advertisement Artificial Intelligence 19
Important achievements in AI (5) ◼ Chess ❑ Deep Blue (IBM computer system) defeated the world chess master Garry Kasparov in 1997 ◼ Problem solving ❑ Computer program PROVERB can solve crossword puzzles better than many people ◼ Self-driving car ❑ A van car is automatically driven by the ALVINN system (CMU) for 98% of the time traveling from Pittsburgh to San Diego (~ 2,850 miles) ◼ Diagnosis ❑ Probability analysis-based medical diagnostic programs can perform at the same level as specialists in some medical areas Artificial Intelligence 20
Important achievements in AI (6) ◼ Robot ❑ Today, many medical surgeries use robotic aids in microsurgery ◼ Automatic scheduling and planning ❑ NASA designed an automatic scheduling program (called Remote Agent) to control the scheduling of spacecraft operations ◼ Logistics planning for the military ❑ During the Gulf war in 1991, U.S. military forces deployed a logistics scheduling and planning program to move 50,000 vehicles, cargo and troops Artificial Intelligence 21
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